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公开(公告)号：US20220398407A1
公开(公告)日：2022-12-15
申请号：US17343975
申请日：2021-06-10
Applicant: Bank of America Corporation
Inventor： MadhuSudhanan Krishnamoorthy , Ramaswamy M
Abstract: A system for removing a noise artifact from an image of a document extracts a first set of features from the image, where the first set of features represents items on the image. The system identifies noise artifact features from the first set of features representing pixel values of the noise artifact. The system generates a second set of features by removing the noise artifact features from the first set of features. The system generates a test clean image of the document based on the second set of features as an input. The system determines whether a portion of the test clean image that previously displayed the noise artifact corresponds to a counterpart portion of the training clean image. If it is determined that the portion of the test clean image corresponds to the counterpart portion of the training clean image, the system outputs the test clean image.
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公开(公告)号：US20240168838A1
公开(公告)日：2024-05-23
申请号：US17990967
申请日：2022-11-21
Applicant: BANK OF AMERICA CORPORATION
Inventor： Durga Prasad Kutthumolu , Saravana Kumar PD , Ramaswamy M , Sakshi Bakshi , Sreekanth Raghuveer Maringanti , Ramakanth Bachu
IPC: G06F11/07
CPC classification number: G06F11/0772 , G06F11/0709
Abstract: Systems, computer program products, and methods are described herein for intelligent exception handling within a distributed network environment. The present disclosure is configured to receive an incidence of a first exception associated with a network interaction; extract information associated with the first exception; determine, via a machine learning (ML) subsystem, a first exception category associated with the first exception based on at least the information associated with the exception; retrieve, from a repository, a first set of actions associated with the first exception category, wherein the first set of actions are configured to resolve the first exception; and in response, execute the first set of actions.
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公开(公告)号：US11783453B2
公开(公告)日：2023-10-10
申请号：US17344360
申请日：2021-06-10
Applicant: Bank of America Corporation
Inventor： MadhuSudhanan Krishnamoorthy , Ramaswamy M
IPC: G06T5/00 , G06N3/08 , G06V30/414 , G06N3/045
CPC classification number: G06T5/002 , G06N3/045 , G06N3/08 , G06V30/414 , G06T2207/20081 , G06T2207/20084
Abstract: A system for adapting an image noise removal model based on a device processing capability receives, from a computing device, a request to adapt an image noise removal module for the computing device. The system compares a processing capability of the computing device with a threshold processing capability. The system determines whether the processing capability is greater or smaller than the threshold processing capability. In response to determining that the processing capability is greater than the threshold processing capability, the system sends a version of the image noise removal module that is adapted for computing devices with processing capabilities less than the threshold processing capability, where the version of the image noise removal module is adapted to have a number of neural network layers less than a threshold number of neural network layers.
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公开(公告)号：US20220398694A1
公开(公告)日：2022-12-15
申请号：US17344360
申请日：2021-06-10
Applicant: Bank of America Corporation
Inventor： MadhuSudhanan Krishnamoorthy , Ramaswamy M
Abstract: A system for adapting an image noise removal model based on a device processing capability receives, from a computing device, a request to adapt an image noise removal module for the computing device. The system compares a processing capability of the computing device with a threshold processing capability. The system determines whether the processing capability is greater or smaller than the threshold processing capability. In response to determining that the processing capability is greater than the threshold processing capability, the system sends a version of the image noise removal module that is adapted for computing devices with processing capabilities less than the threshold processing capability, where the version of the image noise removal module is adapted to have a number of neural network layers less than a threshold number of neural network layers.
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Patent Agency Ranking
公开(公告)号：US11330145B1
公开(公告)日：2022-05-10
申请号：US17344088
申请日：2021-06-10
Applicant: Bank of America Corporation
Inventor： MadhuSudhanan Krishnamoorthy , Ramaswamy M
Abstract: A device for removing a noise artifact from a document receives a scan of the document, where the document contains a noise artifact at least partially obstructing a portion of the document. The device generates an image of the document, and extracts a first set of features from the image. The device identifies noise artifact features from the first set of features, and generates a second set of features by removing the noise artifact features. The device generates a test clean image of the document based on the second set of features. The device determines whether a portion of the test clean image that previously displayed the noise artifact corresponds to a counterpart portion of the training clean image. If it is determined that the portion of the test clean image corresponds to the counterpart portion of the training clean image, the device outputs the test clean image.
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公开(公告)号：US12153486B2
公开(公告)日：2024-11-26
申请号：US17990967
申请日：2022-11-21
Applicant: BANK OF AMERICA CORPORATION
Inventor： Durga Prasad Kutthumolu , Saravana Kumar Pd , Ramaswamy M , Sakshi Bakshi , Sreekanth Raghuveer Maringanti , Ramakanth Bachu
IPC: G06F11/07
Abstract: Systems, computer program products, and methods are described herein for intelligent exception handling within a distributed network environment. The present disclosure is configured to receive an incidence of a first exception associated with a network interaction; extract information associated with the first exception; determine, via a machine learning (ML) subsystem, a first exception category associated with the first exception based on at least the information associated with the exception; retrieve, from a repository, a first set of actions associated with the first exception category, wherein the first set of actions are configured to resolve the first exception; and in response, execute the first set of actions.
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7.发明授权公开(公告)号：US11798136B2
公开(公告)日：2023-10-24
申请号：US17344219
申请日：2021-06-10
Applicant: Bank of America Corporation
Inventor： MadhuSudhanan Krishnamoorthy , Ramaswamy M
IPC: G06T5/00 , G06V30/414 , G06V10/30 , G06V10/75 , G06V10/82 , G06V30/164 , G06V30/41 , G06V30/416 , G06T7/00 , G06V10/98 , G06V30/418
CPC classification number: G06T5/002 , G06T7/97 , G06V10/30 , G06V10/751 , G06V10/82 , G06V10/993 , G06V30/164 , G06V30/41 , G06V30/414 , G06V30/416 , G06V30/418 , G06T2207/10008
Abstract: An Automated Teller Machine (ATM) for detecting security vulnerabilities by removing noise artifacts from documents receives a transaction request when a document is inserted into the ATM, where the document contains a noise artifact at least partially obstructing a portion of the document. The ATM generates an image of the document, where the image displays at least one data item comprising a sender's name, a receiver's name, and a number representing an amount. The ATM determines whether the noise artifact obstructs at least partially one data item. In response to determining that the noise artifact obstructs at least partially one data item, the ATM generates a test clean image of the document by removing the noise artifact from the image. In response to determining that the noise artifact is removed, the ATM approves the transaction request.
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公开(公告)号：US11756285B2
公开(公告)日：2023-09-12
申请号：US17343975
申请日：2021-06-10
Applicant: Bank of America Corporation
Inventor： MadhuSudhanan Krishnamoorthy , Ramaswamy M
IPC: G06T5/00 , G06V10/30 , G06V30/418
CPC classification number: G06V10/30 , G06T5/002 , G06V30/418 , G06T2207/20081 , G06T2207/30176
Abstract: A system for removing a noise artifact from an image of a document extracts a first set of features from the image, where the first set of features represents items on the image. The system identifies noise artifact features from the first set of features representing pixel values of the noise artifact. The system generates a second set of features by removing the noise artifact features from the first set of features. The system generates a test clean image of the document based on the second set of features as an input. The system determines whether a portion of the test clean image that previously displayed the noise artifact corresponds to a counterpart portion of the training clean image. If it is determined that the portion of the test clean image corresponds to the counterpart portion of the training clean image, the system outputs the test clean image.
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9.发明申请公开(公告)号：US20220398900A1
公开(公告)日：2022-12-15
申请号：US17344219
申请日：2021-06-10
Applicant: Bank of America Corporation
Inventor： MadhuSudhanan Krishnamoorthy , Ramaswamy M
Abstract: An Automated Teller Machine (ATM) for detecting security vulnerabilities by removing noise artifacts from documents receives a transaction request when a document is inserted into the ATM, where the document contains a noise artifact at least partially obstructing a portion of the document. The ATM generates an image of the document, where the image displays at least one data item comprising a sender's name, a receiver's name, and a number representing an amount. The ATM determines whether the noise artifact obstructs at least partially one data item. In response to determining that the noise artifact obstructs at least partially one data item, the ATM generates a test clean image of the document by removing the noise artifact from the image. In response to determining that the noise artifact is removed, the ATM approves the transaction request.
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